coastal upwelling indices, west coast of north america, 1946-95

NOAA Technical Memorandum NMFSThis TM series is used for documentation and timely communication of preliminary results, interim reports, or specialpurpose information. The TMs have not received complete formal review, editorial control, or detailed editing.

1996

COASTAL UPWELLING INDICESWEST COAST OF NORTH AMERICA

1946-95

Franklin B. Schwing

Michael O’Farrell

John M. Steger

Kenneth Baltz

Pacific Fisheries Environmental LaboratorySouthwest Fisheries Science Center

1352 Lighthouse AvenuePacific Grove, California 93950-2097

NOAA-TM-NMFS-SWFSC-231

U.S. DEPARTMENT OF COMMERCE

National Oceanic and Atmospheric Administration

National Marine Fisheries Service

Abstract

Long time series of ocean surface currents are not available, however reasonable

estimates of surface transport and coastal upwelling may be made using planetary

boundary layer theory and the geostrophic wind approximation. PFEG generates daily

and monthly indices of coastal upwelling at 15 standard geographic points along the

west coast of North America. The first set, beginning in 1967, is comprised of daily

means of six-hourly upwelling indices, estimated from six-hourly synoptic pressure fields.

The second set of indices are derived from monthly-mean pressure fields, and extend

back over 50 years to 1946.

The annual cycle is estimated at each point by a least-squares regression of the

1967-91 daily data to an annual and semiannual harmonic signal. The means and

standard deviations of monthly values are calculated for the same 25-year period to

compare their annual climatologies to those from the daily indices. Upwelling north of

30oN has a strong annual signal. Greatest upwelling rates occur at 33oN, with a linear

decrease in the maximum upwelling indices north to about 54oN. The greatest annual

range occurs at 39oN. The date of maximum upwelling increases linearly from late April

at 21oN to mid-July at 48oN. Minima occur within 15 days of 1 January at all latitudes,

with negative (downwelling-favorable) indices occurring north of 36oN during at least

part of the year. Downwelling is a year-around feature along the British Columbia

coast. The annual range off Baja California is relatively small. This region is also

characterized by secondary minima and maxima in August and October, respectively.

Highest interannual variance at a location occurs during months of greatest absolute

index values. Variance south (north) of 45oN is greatest in summer (winter).

Indices derived from monthly pressure fields are consistently greater than monthly

averages of the daily indices. This discrepancy is greatest during winter downwelling at

northern points, and summer upwelling at southern points. Daily standard errors are

consistently greater than the associated monthly deviations, due to the high variability

on a given Julian day associated with synoptic atmospheric motions. Monthly standard

deviations off central and southern California peak in spring and remain relatively high

through the summer, while daily standard errors decline rapidly between late winter

and summer.

One of the most striking highlights is the relatively short duration of significant

positive and negative anomalies (< 1 year), despite the large latitudinal extent of most

anomalies. The indices also feature sudden shifts in their temporal patterns. These

may be attributed to changes in the source of the monthly pressure fields, or in the

methodology used to interpolate the gridded pressure fields used to calculate these

indices, rather than true environmental changes.

2

Introduction

The frictional stress of equatorward wind on the ocean’s surface, in concert with

the earth’s rotation, causes water in the surface layer to move away from the western

coast of continental land masses (Sverdrup et al. 1942, p. 501). The offshore moving

surface water, referred to as Ekman transport after the scientist who first described

this process, is replaced by water which upwells along the coast from depths of 50-100

m and more. Upwelled water is cooler and more saline than the original surface

water (Robinson 1976; Huyer 1983; Kosro et al. 1991) and typically has much greater

concentrations of nutrients such as nitrate, phosphate and silicate that are key to

sustaining biological production (Smith 1968; Traganza et al. 1981; Kosro et al. 1991).

This is why marine ecosystems in eastern boundary currents are highly productive,

and capable of maintaining large standing crops of plankton, massive fish stocks such

as sardines and anchovies, and major populations of marine mammals and sea birds

(Cushing 1969; Ryther 1969; Walsh et al. 1977; Wroblewski 1977). The major eastern

boundary currents include the Canary off the Iberian peninsula and northwestern

Africa, the Benguela off southwestern Africa, the Peru (or Humboldt) off western South

America, the Leeuwin off western Australia, and the California Current System off

western North America. Moreover variations in upwelling over seasonal to interannual

and longer periods, due to large-scale shifts in wind patterns and atmospheric systems,

are linked to variability in fish populations and other biological components in coastal

ocean ecosystems (Parrish et al. 1981; Cury et al. 1995; Parrish and Mallicoate 1995).

Each month, the Pacific Fisheries Environmental Group (PFEG) generates indices

of the intensity of large-scale, wind-induced coastal upwelling at 15 standard locations

along the west coast of North America (Figure 1). The indices are based on estimates

of offshore Ekman transport driven by geostrophic wind stress. Geostrophic winds are

derived from six-hourly synoptic and monthly mean surface atmospheric pressure fields.

The pressure fields are interpolated from surface observations and provided by the U.S.

Navy Fleet Numerical Meteorology and Oceanography Center (FNMOC), Monterey,

CA.

Directly quantifying upwelling is extremely difficult, and observed time series of the

phenomenon do not exist. The idea behind the upwelling index was to develop some

simple time series that represent variations in upwelling along the coast. Wooster and

Reid (1963) demonstrated that the offshore component of surface Ekman transport

represents an “index of upwelling” that describes seasonal variability in near-coastal

cooling presumably associated with upwelling. Although long-term time series of ocean

surface currents are not available, reasonable estimates of surface transport may be

made using the geostrophic wind approximation and planetary boundary layer theory.

PFEG regularly produces and provides daily and monthly index time series to scientists

3

110°130°

40°

20°

60°N

150°W

60N 149W 60N 146W

57N 137W

54N 134W

51N 131W

48N 125W

45N 125W

42N 125W

39N 125W

36N 122W

33N 119W

30N 119W

27N 116W

24N 113W

21N 107W

l ,f +h

l +h,f

l ,f -h

l -h,fh

h

4

Figure 1. Map showing 3o extrapolated mesh (small open circles) for pressure fields used to derive the upwelling indices. Large open circles denote locations of the 15 standard near-coastal positions of the indices reported here. Inset shows discretization scheme used to estimate geostrophic winds from pressure gradients (Equations 1 and 2).

and managers concerned with marine ecosystems and their biota. The indices arecurrently distributed to about 50 regular users each month, and each year another40-50 individuals request upwelling data or information on how they are derived. Thedistribution of users by their afiliation is shown in Figure 2. The chart on the leftrepresents the distribution of individuals receiving upwelling index data on a monthlybasis, while the chart on the right denotes the afiliation of individuals who haverequested data or information since 1984.

These series have been used in scores of studies and scientific publications; over 400publications refer to the Bakun (1973) technical memorandum that initially describedthe upwelling indices. Examples include studies to describe coastal circulation (Bakunand Nelson 1977; Huyer 1983; Hayward et al. 1995; Thomson and Ware 1996); ENSO(Huyer and Smith 1985); and climate change (Bakun 1990; van Geen and Husby1996); as well as in understanding the linkages between environmental and biologicalvariability; zooplankton (Peterson and Miller 1977; Brodeur and Ware 1992), crabs(Botsford and Wickham 1975; McConnaughey et al. 1992), groundfish (Ainley et al.1993; VenTresca et al. 1995), small pelagics (Parrish and MacCall 1978; Cury and Roy1989; Parrish and Mallicoate 1995), salmon (Nickelson 1986; Fisher and Pearcy 1988;Hiss 1995), and marine birds (Ainley et al. 1993, 1995).

5fl

MONTHLY DISTRIBUTION

ACADEMICFOREIGN

STATEGOVT

OTHERFEDERAL

GOVTOTHERNOAA

NOAANMFS

PRIVATE

SPECIAL REQUESTS

ACADEMIC

FOREIGN

STATEGOVT

OTHERFEDERAL

GOVTOTHERNOAA

NOAANMFS

PRIVATE

Figure 2. Charts showing the distribution of users of upwelling index data and related information,by their type of affiliation. Left hand chart shows distribution of individuals receiving upwelling products on a monthly basis. Right hand chart shows distribution of special requests for upwelling products or information.

PFEG coastal upwelling indices are calculated based upon Ekman’s (1905) theory

of mass transport due to wind stress. Assuming homogeneity, uniform wind, and steady

state conditions, the mass transport of surface water due to wind stress is 90o to the

right of the wind direction in the Northern Hemisphere. Ekman mass transport is

defined as the wind stress divided by the Coriolis parameter. The depth to which an

appreciable amount of this offshore transport occurs is termed the surface Ekman layer,

and is generally 50-100 m deep.

Ekman transports are resolved into components parallel and normal to the local

coastline orientation. The magnitude of the offshore component is considered to be

an index of the amount of water upwelled from the base of the Ekman layer. Positive

values are, in general, the result of equatorward wind stress. Negative values imply

downwelling, the onshore advection of surface waters accompanied by a downward

displacement of water.

History of the Upwelling Index

PFEG began computing the upwelling indices in the early 1970’s. Six-hourly

synoptic surface pressure analyses from FNMOC, originally known as Fleet Numerical

Weather Central and later as Fleet Numerical Oceanographic Center, were used to

calculate two sets of upwelling index time series. One set is comprised of daily and

weekly means of six-hourly upwelling indices, estimated from the FNMOC six-hourly

synoptic pressure fields. Availability of synoptic data prior to 1967 is much more

limited. The second set of indices are monthly time series derived from monthly-mean

pressure fields, and extend back to 1946. The synoptic fields used to construct the

monthly mean fields prior to July 1962 were acquired from a variety of sources (Bakun

1973), rather than FNMOC.

Bakun (1973) initially described the methods used to calculate the upwelling

indices, and presented monthly, quarterly, and annual indices for 15 near-coastal

positions along the North American west coast for the period 1946-71. Daily and weekly

means of the upwelling indices at these standard west coast locations were published by

Bakun (1975) for the period 1967-73. A third report in the series (Mason and Bakun

1986) summarizes the monthly indices for 1946-71, along with daily and weekly means

of the six-hourly indices for 1974-85 at six locations along the U.S. west coast (33-48oN).

Because of differences in the averaging period of the pressure fields, the daily and

monthly series are not numerically equivalent nor directly interchangeable (cf. average

annual cycles derived from daily and monthly values).

6

Methods

Bakun (1973) describes the computations for deriving the upwelling indices. Due to

limited availability of that publication, the assumptions and calculations will be detailed

here as well.

Historically, six-hourly and monthly mean pressure fields prepared by FNMOC on

a 63 × 63 point square grid were superimposed onto a polar-stereographic projection

of the Northern Hemisphere. The mesh length of this projection is 200 nm (370 km)

at 60oN and decreases southward to about 144 nm (267 km) at 20oN. These data

were then extrapolated to a 3o mesh length on a spherical coordinate system using

Bessel’s central difference formula, to standardize the spacing of the pressure fields in

subsequent derivations. After providing PFEG with several alternate pressure field grids

over time, FNMOC currently produces six-hourly fields of surface pressure on a global

spherical 1o mesh (a 180 × 360 grid). The standard west coast six-hourly upwelling

indices are a product of the 3o pressure field interpolated from the global spherical

1o grid. The monthly indices are derived from a 3o mesh that is interpolated from

the monthly-averages of the six-hourly 1o pressures. The 3o mesh for western North

American and the Northeast Pacific, and the location of the 15 standard locations, is

illustrated in Figure 1.

First derivatives of surface pressure P at each grid point are estimated by taking

the difference in pressure between the grid points to either side and dividing by the 6o

angular mesh length (Figure 1 inset).

δP

δφ∼=

Pλ,φ+h − Pλ,φ−h

2h;

δP

δλ∼=

Pλ+h,φ − Pλ−h,φ

2h; (1)

where φ and λ are the north and east angular coordinates, respectively, and h is the 3o

mesh length in radians.

The east (ug) and north (vg) components of the geostrophic wind are:

ug = − 1

fρaR

δP

δφ; vg = +

1

fρaRcosφ

δP

δλ; (2)

where f is the Coriolis parameter, ρa is the density of air (assumed constant at 1.22

kg/m3), and R is the mean radius of the Earth.

Assuming no friction, the geostrophic wind is parallel to local isobars, with low

pressure to the left in the Northern Hemisphere; i.e., wind circulates counter-clockwise

(cyclonic) around Northern Hemisphere atmospheric lows. To approximate frictional

effects, the geostrophic wind at the sea surface is estimated by rotating the geostrophic

wind 15o to the left and reducing its magnitude by 30%.

7

Sea surface wind stress is calculated from the geostrophic wind using the classic

square-law formula:

~τ = ρaCd|~v|~v (3)

where ~τ is the wind stress vector, ρa is the air density, Cd is an empirical drag coefficient,

and ~v is the estimated wind vector near the sea surface with magnitude |~v|. A Cd

of 0.0013 is used to calculate upwelling from the six-hourly surface pressure fields;

the Cd is increased to 0.0026 when the monthly-mean pressure data is used. Nelson

(1977) describes in detail why a larger Cd is necessary for the monthly calculations,

but basically the monthly averaging of pressure smooths out synoptic atmospheric

stability, storm energy, ocean roughness due to waves, etc. (Davidson 1974), as well as

observations error. Doubling the Cd is an attempt to account for these differences.

The Ekman transport, ~M , is calculated using:

~M =1

f~τ × ~k (4)

where ~k is the unit vector directed vertically upward.

The sign of the offshore component of the Ekman transport, Mx = τ y/f , where x is

normal and y parallel to the local coastline orientation, is then reversed to reflect that

negative (offshore) Ekman transport leads to positive (upwelling) vertical transport, and

positive (onshore) Ekman transport leads to negative (downwelling) vertical transport.

The upwelling indices are expressed in units of cubic meters per second per 100 meters

of coastline, which is equivalent to metric tons/s/100 m coastline. These values are an

index of large-scale coastal upwelling, a mean value representative of mass transport

averaged spatially over approximately 200 nautical miles. Small-scale upwelling and

downwelling events unresolved by the upwelling indices time and space scales may occur

during the averaging period for a particular location.

Caveats

Bakun (1973, 1975) and Mason and Bakun (1986) discuss several caveats for the

users of the upwelling indices. As described above, the daily and monthly indices are

computed using different Cd values (Equation 3) and are not numerically equivalent.

However there is considerable spatial inhomogeneity in the relationship between the

daily and monthly series (Bakun 1973). A similar degree of seasonal and interannual

variability occurs as well, as seen in the figures in Appendix A. Thus the use of a single

adjusted Cd does not completely rectify this discrepancy, and comparisons of these data

sets should be done with caution.

The previous reports also point out that the resolution of the gridded pressure fields

does not resolve the short correlation scale of the atmosphere near coastal topography.

8

Bakun (1973) suggests this may lead to artificially high geostrophic winds adjacent to

coastal mountain ranges. On a related issue, the distribution of individual pressure

observations within an area will not be uniform in space or time, so the available

information may misrepresent the true averaged pressure for a grid point at a given

time. The patterns and total number of observations will change over time as well,

imparting artificial trends or fluctuations in the series.

In addition, at least four different agencies have supplied pressure fields to allow

PFEG to construct the 50-year series available today. Differences in the data and

methods used by each to produce these fields appear to induce clear changes in the

upwelling time series. FNMOC, who currently supplies the pressure fields, has changed

the algorithms employed in generating their pressure fields at various times. This also

appears to affect the derived indices. These changes should be taken into account when

analyzing long-term trends or variations in the upwelling time series.

While the derivations of the indices are based on established theory, they are

nonetheless a simplified and incomplete representation of the physics that drive coastal

circulation and specifically Ekman transport. Upwelling is due to the combined effect of

two processes; coastal upwelling (the process that is the basis of the indices described

here) and Ekman pumping (wind curl, or the spatial variation in the wind). The

latter process may be an equally important contributor to surface Ekman divergence

and upwelling (Bakun and Nelson 1991), thus the reader is cautioned that the data

presented here may not represent the true amount of upwelling. In addition, the

calculations are based on numerous assumptions and simplified parameterizations, to

ease computation and, in some cases, because we can only approximate the true physical

world at this point. Future research will no doubt reveal formulations that will improve

our representation of coastal dynamics. However the calculations applied in this case do

provide a reasonable representation of Ekman transport in the coastal zone, given our

current state of knowledge.

Results

A thorough analysis and interpretation of this 50-year record of upwelling indices

is beyond the scope of a technical memorandum, but a few details of these data will be

highlighted. The reader will find considerable insight from examination of the figures

in this report, and we anticipate it will inspire further studies. The daily, weekly

and monthly upwelling indices, and their climatologies, are summarized in a series of

appendices.

The means and standard deviations of monthly values are calculated for each

calendar month for the 25-year period, 1967–91. These are summarized in Figure 3,

shown by position in Appendix A, and contoured as a function of time and latitude in

9

Figure 3. a) Average monthly upwelling index contoured by position and month. Average is for 1967-91.b) Standard deviation of monthly indicies for the same period. c) Biharmonic fit to daily data for 1967-91.d)Standard error of daily indicies for same period. All data contoured by position and time. Dark greenvalues denote higher upwelling values and variance. Units are in m3/s/100m

10

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-50

0

50

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350

0

10

20

30

40

50

60

70

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90

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AVERAGE MONTHLY UPWELLING INDEX 60N 149W60N 146W57N 137W54N 134W51N 131W48N 125W45N 125W42N 125W39N 125W36N 122W33N 119W30N 119W27N 116W24N 113W21N 107W

60N 149W60N 146W57N 137W54N 134W51N 131W48N 125W45N 125W42N 125W39N 125W36N 122W33N 119W30N 119W27N 116W24N 113W21N 107W

MONTHLY STANDARD DEVIATION

0

20

40

60

80

100

120

140

160

J F M A M J J A S O N D

J F M A M J J A S O N DJ F M A M J J A S O N D

J F M A M J J A S O N D

BIHARMONIC DAILY UPWELLING INDEX

DAILY STANDARD ERROR

-200

-150

-100

-50

0

50

100

150

200

250

300

350

Appendix C. These values are also used to calculate anomalies from the means of the

calendar months (Appendices B, C, and D). Standard anomalies, the anomalies divided

by the standard deviation for the calendar month, are contoured in Appendix C.

The upwelling maximum is centered along southern California during summer

(Figure 3a). Minima occur at all latitudes in the winter, with negative (downwelling-

favorable) means occurring north of 36oN during at least one month of the year.

Downwelling is a year-round feature along the British Columbia coast. Times of

greatest absolute monthly indices at a location correspond closely with the months of

highest interannual variation (Figure 3b). Standard deviations south (north) of 45oN

are greatest in summer (winter). The greatest summer variance (ca. 39oN) coincides

with the maximum spatial gradient in the mean index, suggesting that interannual

shifts in the position of strongest upwelling, rather than in the timing of the upwelling

cycle, are responsible for the high standard deviations. The latitude of the highest

temporal gradients (33oN) does not have corresponding high standard deviations,

further supporting this idea. In contrast, the highest winter deviations do not occur in

a region of high spatial or temporal gradients. Thus the more likely explanation for

the winter variability is interannual differences in the large-scale subarctic pressure field

(e.g., variability in the Aleutian Low), rather than shifts in the timing or position of

maximum downwelling wind conditions.

Because the annual upwelling cycle is roughly sinusoidal, the shape of the annual

cycle is estimated at each of the 15 grid points by a least-squares regression of the daily

data from 1967–91 to an annual and semiannual harmonic signal (Lynn et al. 1967;

Hayward et al. 1995). The biharmonic equation is of the form

UI(t) = A0 + A1 cos(2πt) + B1 sin(2πt) + A2 cos(4πt) + B2 sin(4πt) (5)

where t is the Julian Day/365 and the Ai and Bi are coefficients determined by the

regression for each point, given in Table 1. The fits are not improved significantly by

including higher harmonics. Identical 25-year periods were selected for the daily and

monthly data to provide an intercomparison of their annual climatologies (Appendix A).

Standard errors were calculated for each Julian Day, then fit with the same biharmonic

model (Equation 5). The daily harmonic indices and standard errors are contoured as

a function of latitude in Figures 3c and 3d, respectively. The biharmonic fits also are

regressed against the original 25-year subseries, and against the 25-year subseries that

have been low-passed with a Chebychev Type I fifth-order filter with a 30-day cutoff

(Table 1). To give an example of the degree of variability in the daily values, the annual

biharmonic cycle ± 1 standard error determined at 39oN, 125oW is superimposed on the

daily indices from 1967–91 (Figure 4). The last column of Table 1 gives R′, the ratio of

the variance squared from the unfiltered and low-passed daily fits. Higher values of R′

11

Figure 4. Annual biharmonic fits to daily upwelling indices at 39oN, 125oW (bold curve), +/- one standard error for each Julian Day (shaded area), for period 1967-91. Dots denote individual daily index values for same period. Units are m3/s/100m.

13

39N 125W

0 50 100 150 200 250 300 350-500

-400

-300

-200

-100

0

100

200

300

400

500

denote locations where the amount of high-frequency (synoptic) variance is relatively

large compared to low-frequency (interannual) variance.

The characteristics of the annual upwelling cycle at each point, based on the

biharmonic fit to the 1967–91 daily values, are summarized in Figure 5. The North

American west coast appears to break down into three distinct upwelling regions; Baja

California (21–30oN), continental US (30–48oN), and British Columbia and Alaska

(48–60oN). The annual range off Baja California is relatively small, with wintertime

values of less than 50 m3/s/100m and summer maxima of 75-150 m3/s/100m. The

timing of strongest upwelling increases from late April at 21oN to late May at 30oN.

The time of minimum upwelling occurs within about ±15 days of 1 January, a pattern

repeated the length of the coast. This region is also characterized by secondary minima

and maxima in August and October, respectively (more technically a pair of inflection

points in the annual curves at 27oN and 30oN). In contrast, annual cycles north of

30oN have a strong sinusoidal (12-month harmonic) signature. The greatest upwelling

rates occur at 33oN, with a linear decrease in the maximum upwelling indices north to

about 54oN. The greatest annual range occurs at 39oN. The timing of the maximum

continues the appearance of northward propagation, with maximum rates off Oregon

and Washington lagging those at 21oN by about 80 days (ca. 25 km/d). Maximum

values north of Washington are about zero, and occur in June–July. Minimum indices

of about -100 m3/s/100m occur in ca. 1 January.

The phase of maximum upwelling corresponds with climatological surface conditions

along the coast (Lynn 1967). Maximum salinity occurs in May off northern Baja,

June-July off southern California, and July and August along central California (ca.

36–38oN). Salinity maxima along southern Baja occur in fall, coinciding with the

secondary upwelling maximum. The temperature mimima found by Lynn in upwelling

regions, typically in April–May, is impacted substantially by the seasonal surface heat

flux and agrees less well with the time of greatest upwelling. The relationship between

the annual cycle of upwelling and temperature and salinity is also complicated by

advection along the coast, and is influenced by the surface water masses of the California

Current.

Annual cycles for the daily and monthly data sets are compared in Figure 3, and

in a series of plots in Appendix A. It appears that upwelling indices derived from

monthly pressure fields overestimate the magnitude of upwelling and downwelling based

on monthly averages of the daily values. This discrepancy is most evident during

the months of the highest absolute values at each location (e.g., monthly indices

overestimate winter downwelling at the northern points, and summer upwelling at

the southern points). Bakun (1973) discusses the disparity between the daily and

monthly indices, and shows the monthly values underestimate the monthly means of

the six-hourly Ekman transports by as much as 50%, provided the same value of Cd is

14



-200 -100 0 100 200

AMPLITUDE

PHASE

MAXIMUM

MINIMUM

MAXIMUM

MINIMUM

2nd MAXIMUM

2nd MINIMUM

1 JAN1 NOV1 SEP1 JUL1 MAY

B

B

J

J

B

B

B

B

B J

J

J

J

B

B

B

B

B

B

B

B

B

B

J

J

J

J

B

B

B

B

B

B

B

B

B

B

B

B

B

B

B

B

B

B

B

B

B

B

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B

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B

B

B

B

B

B

BB

B

BB

B

B

B

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B

B

B

B

B

B

B

15

Figure 5. Characteristics of annual cycle of daily upwelling, based on biharmonic fits for period 1967-91. Upper panel shows maximum and minimum amplitudes of annual cycle at each position. Lower panel shows calendar dates of maxima and minima at all locations, and secondary maxima and minima for 21-30oN. Units are m3/s/100m.

used for both (Equation 3). Bakun showed this distortion varies with location as well.

Put another way, doubling the Cd in the monthly stress calculations leads to a 130%

overestimate of the daily upwelling rates off Alaska, and a factor of two overestimate off

southern and Baja California. In addition, Bakun had only 54 months of data available

for comparison, so his analysis could not consider whether these differences have a

seasonal effect. With 25 years of simultaneous daily and monthly data now available,

our preliminary interpretation, as reflected in Figure 3 and Appendix A, is that the

relative discrepancy between the two data sets varies with season as well as latitude. We

are currently developing a more complete analysis that will hopefully allow the monthly

indices to be adjusted temporally and spatially to reflect more realistic estimates of

coastal upwelling.

The annual pattern of the daily standard errors separates into geographic regions.

Winter conditions are much more variable than summer north of 39oN. Variance is more

evenly distributed throughout the year from 24–39oN, with slightly elevated standard

errors in spring and a late summer minimum. The seasonal pattern is particularly flat

along Baja. The southernmost site is unique in its unusually high variance in late

spring, possibly an artifact of changes in the pressure field model used by the Navy.

A comparison between the standard errors of the daily values and the monthly

standard deviations reveals some interesting differences (Figure 3). Since s.e. = s.d./√

n,

where n is the sample size, 25 in this case, the standard errors are consistently and

substantially greater than the associated monthly deviations. The difference is due

to the high degree of variability on a given day associated with synoptic atmospheric

motions. These are averaged out in the monthly pressure fields; the monthly deviations

reflect large-scale interannual variations while the daily variance is a combination of

random storminess in addition to interannual differences. The quantitative differences

between these two estimates of variance at a location is therefore an indication of the

relative contribution of synoptic and interannual variations. Areas north of 42oN and

south of 33oN feature similar annual patterns. Off central and southern California

however monthly standard deviations peak in spring and remain relatively high through

the summer, while daily standard errors decline rapidly between late winter and

summer. This difference is particularly strong at 39oN. Relatively greater wintertime

synoptic energy at these latitudes is reflected in the dramatically different annual cycles

in daily versus monthly variance. This pattern also agrees with the spatial distribution

of R′ (Table 1).

The anomalies of the monthly upwelling indices, relative to the 25-year mean of the

monthly values for 1967–91, are presented for each location in Appendix B. Means and

standard deviations for each calendar month are also given at the bottom of each page.

16

In Appendix C, plots of the monthly upwelling indices, the monthly anomalies, and

the anomalies normalized by the standard deviations for each calendar month are shown.

The continuity of anomalies in time and space can be seen in this format The data are

broken into five ten-year periods for ease of presentation. The anomalies plotted here

are given in the tables in Appendix B. One of the most striking highlights of these

figures is the relatively short duration of significant positive and negative anomalies,

despite the large spatial extent of most of the anomalies. Strong ENSO events (e.g.,

1957, 1983, 1992) correspond to significant negative anomalies along much of the U.S.

coast. Positive and negative upwelling anomalies correspond closely to cool and warm

coastal SST anomalies, respectively, calculated by Cole and McLain (1989) for the

period 1971–87, suggesting that SST interannual variability is related to differences in

coastal upwelling, which is approximated reasonably well by these indices.

Anomalies of monthly upwelling indices, as given in Appendix B, are plotted as

50-year time series for each location in Appendix D. Again the short duration of large

anomalies (typically a few months) is apparent. These time series also display the

spatial coherence of many of the anomalies. These series also feature sudden shifts in

the temporal pattern of the indices. One example is the relatively poor fit of the annual

mean prior to 1955 off southern California, reflected in the apparently large annual

signal in the anomalies. Another example is the dramatic change in 1976 at 21oN,

which is due to a shift in the summer indices. These changes are also apparent in the

anomalies in Appendix B and in the contour plots in Appendix C. These changes in the

patterns of the indices are questionable, and may be attributed to changes in the source

of the monthly pressure fields (Bakun 1973), or in the methodology used to interpolate

the gridded pressure fields used to calculate these indices.

The final set of figures (Appendix E) contains a series of plots, by year, of daily and

weekly-averaged upwelling indices for 1986–1995. Superimposed on each figure is the

annual biharmonic fit to the daily indices for that location. The shaded area covers ±one standard error from the mean. Periods of anomalously strong and weak upwelling

and downwelling, typically on the time scales of storms and other atmospheric events,

can be quickly identified in these figures as outliers from the standard error envelope.

The plots are separated by location.

Modernization

Rapid advancements in computing and communications since the initial development

of the upwelling index over two decades ago have led to more accurate and efficient

calculation and distribution of the products described here. Several factors contribute to

improved data quality and more timely distribution. Collection of surface pressure data

is now more routine and the oceans are now covered more completely with observations

17

than in the past. Models employed by the Navy to interpolate the gridded fields

from observations have been improved. High-speed desktop computers, high-resolution

printers, and modern graphics software are now available to produce the data products

efficiently, economically and with much higher quality. Finally, new telecommunication

methods and procedures such as e-mail, file transfer protocol (ftp), and the Internet,

allow large volumes of data and model output to be transferred between computers,

stored more efficiently and securely, and processed in a more portable fashion. Hard

copy delivery is rapidly giving way to electronic transmission of the upwelling indices and

products, which provides scientists and managers much quicker access to information

than in the past. Within the next year, we envision having the upwelling indices

and many other PFEG data products available on our world-wide web home page

(http:/www.pfeg.noaa.gov). This will make information easily accessible to a wider

spectrum of users as soon as it is generated.

We are also looking at ways to improve the value of the upwelling index. First,

differences between the daily and monthly indices as a function of time and location are

being analyzed in greater detail, which will allow the monthly indices to be adjusted

to represent coastal upwelling rates more realistically. Alternative derivations of

upwelling are being evaluated (e.g., including frictional effects and the role of wind

curl). While these factors may be less critical at the standard points summarized here,

such modifications certainly will be important in other ocean regions. Other analyses

are relating the upwelling index time series to series based on measured winds, as well

as other environmental variables that represent upwelling (e.g., coastal sea level, SST).

This will lead to a better understanding of how well the indices actually represent

coastal upwelling. Finally, we will continue to interact with researchers using the indices

to link environmental and fisheries variability, to learn where these series may not be

biologically relevant and, more generally, what type of information may be most useful

to them. All these improvements will contribute to the long-term goal of producing

an environmental index that has greater utility for biologists, fisheries scientists and

resource managers.

While the upwelling indices described here are by far the most popular product that

PFEG derives from the surface pressure fields, they are but one of several atmospheric

and oceanic products presently generated from the six-hourly pressures. The following

derived fields are currently available from PFEG for the 15 standard points and the

entire North Pacific and Atlantic Oceans on 3o and 5o grids:

SEA LEVEL PRESSURE

SURFACE GEOSTROPHIC WIND VECTOR (east and north components)

SURFACE WIND STRESS VECTOR (east and north components)

CURL OF WIND STRESS

18

Phaedra Green Jessen

http:/www.pfeg.noaa.gov).

http://www.pfeg.noaa.gov

CUBE OF WIND SPEED

EKMAN TRANSPORT VECTOR (east and north components)

OFFSHORE EKMAN TRANSPORT COMPONENT

DIRECTON OF OFFSHORE EKMAN TRANSPORT COMPONENT

VERTICAL VELOCITY INTO EKMAN LAYER

SVERDRUP TRANSPORT

In addition, the following fields are generated for the entire North Pacific:

TOTAL SURFACE TRANSPORT (east and north components)

TOTAL INTEGRATED TRANSPORT

INTEGRATED GEOSTROPHIC TRANSPORT

While all of these fields are based on fundamental physical theory, most have not

been analyzed nor applied to scientific problems. It is our hope to conduct a critical

analysis of these other products and promote their use by researchers and managers.

A future technical memorandum is planned that will summarize some of the more

important products. In the interim, they are available to interested parties, and we

encourage their use.

Acknowledgments

The upwelling indices are a product of years of development and improvement

by scores of individuals. We are indebted to Andrew Bakun for originally developing

the upwelling index, commonly referred to as the Bakun index. James Johnson,

Gunter Seckel, and Douglas McLain provided advice in its initial development. David

Husby, Craig Nelson, Richard Parrish, Roy Mendelssohn, Jerrold Norton, Arthur

Stroud, and George Boehlert are among our many former and current colleagues at

PFEG who contributed advice, stimulating discussion and valuable information, and

suggested improvements. David Cole, Christie Johnson Sharp, and Heather Parker

are acknowledged for their efforts in producing and distributing these indices each

month. Tone Nichols is particularly recognized for generating most of the graphics

and for her technical support. David VenTresca (California Department of Fish and

Game, Monterey) and Ronald Lynn (NMFS Southwest Fisheries Science Center, La

Jolla) graciously reviewed this manuscript. Analyzed digital atmospheric pressure data,

computing and graphical facilities, and considerable logistical support were provided

by U.S. Navy, Fleet Numerical Meteorology and Oceanography Center. Finally, we are

grateful to the many scientists who have applied the indices in their research, and have

given us valuable suggestions for their improvement.

19

References

Ainley, D.G., W.J. Sydeman, R.H. Parrish, and W.H. Lenarz. 1993. Oceanic factors

influencing occurrence patterns of young rockfish Sebastes in central California:

a predator’s perspective. Calif. Coop. Oceanic Fish. Invest. Rep. 34:133-139.

Ainley, D.G., W.J. Sydeman, and J. Norton. 1995. Upper trophic level predators

indicate interannual negative and positive anomalies in the California Current

food web. Mar. Ecol. Prog. Ser. 118:69-79.

Bakun, A. 1973. Coastal upwelling indices, west coast of North America, 1946-71. U.S.

Dep. Commer., NOAA Tech. Rep., NMFS SSRF-671, 103 p.

Bakun, A. 1975. Daily and weekly upwelling indices, west coast of North America,

1967-73. U.S. Dep. Commer., NOAA Tech. Rep., NMFS SSRF-693, 114 p.

Bakun, A. 1990. Global climate change and intensification of coastal ocean upwelling.

Science 247:198-201.

Bakun, A. and C.S. Nelson. 1977. Climatology of upwelling related processes off Baja

California. Calif. Coop. Oceanic Fish. Invest. Rep. 19: 107-127.

Bakun, A. and C.S. Nelson. 1991. The seasonal cycle of wind-stress curl in subtropical

eastern boundary current regions. J. Phys. Oceanogr. 21:1815-1834.

Brodeur, R.D. and D.M. Ware. 1992. Long-term variability in zooplankton biomass in

the subarctic Pacific Ocean. Fish. Oceanogr. 1:32-38.

Botsford, L.W. and D.E. Wickham. 1975. Correlation of upwelling index and Dungeness

crab catch. Fish. Bull. 73:901-907.

Cole, D.A. and D.R. McLain. 1989. Interannual variability of temperature in the

upper layer of the north Pacific eastern boundary region, 1971-1987. U.S. Dep.

Commer., NOAA Tech. Rep., NOAA-TM-NMFS-SWFC-125, 9 p. + figs.

Cury, P. and C. Roy. 1989. Optimal environmental window and pelagic fish recruitment

success in upwelling areas. Can. J. Fish. Aquat. Sci. 46:670-680.

Cury, P., C. Roy, R. Mendelssohn, A. Bakun, D.M. Husby, and R.H. Parrish. 1995.

Moderate is better: exploring nonlinear climatic effects on the Californian

northern anchovy (Engraulis mordax). In R.J. Beamish (ed.), Climate Change

and Northern Fish Populations. Can. Spec. Publ. Fish. Aquat. Sci. 121, p.

417-424.

Cushing, D.H. 1969. Upwelling and fish production. FAO Fish. Tech. Paper 84. 40 p.

Davidson, K.L. 1974. Observational results on the influence of stability and wind-wave

coupling on momentum transfer and turbulent fluctuations over ocean waves.

Boundary-Layer Met. 6:305-331.

Ekman, V.W. 1905. On the influence of the earth’s rotation on ocean currents. Ark.

Mat. Astron. Fys. 2(11):1-52.

Fisher, J.P. and W.G. Pearcy. 1988. Growth of juvenile coho salmon (Oncorhynchus

20

kisutch) off Oregon and Washington, USA, in years of differing coastal upwelling.

Can. J. Fish. Aquat. Sci. 45:1036-1044.

Hayward, T., D. Cayan, P. Franks, R. Lynn, A. Mantyla, J. McGowan, P. Smith, F.

Schwing and E. Venrick. 1995. The state of the California Current in 1994-1995:

a period of transition. Calif. Coop. Oceanic Fish. Invest. Rep. 36: 19-39.

Hiss, J.M. 1995. Environmental Factors Influencing Spawning Escapement of Dungeness

River pink salmon (Oncorhynchus gorbuscha) 1959-1993. USFWS, Western

Washington Fishery Resource Office, Olympia, WA. 50 p.

Huyer, A. 1983. Coastal upwelling in the California Current. Prog. Oceanogr.

12:259-284.

Huyer, A. and R.L. Smith. 1985. The signature of El Nino off Oregon, 1982-1983. J.

Geophys. Res. 90:7133-7142.

Kosro, P.M., A. Huyer, S.R. Ramp, R.L. Smith, F.P. Chavez, T.J. Cowles, M.P. Abbott,

P.T. Strub, R.T. Barber, P. Jessen, and L.F. Small. 1991. The structure of

the transition zone between coastal waters and the open ocean off northern

California, winter and summer 1987. J. Geophys. Res. 96:14707-14730.

Lynn, R.J. 1967. Seasonal variation of temperature and salinity at 10 meters in the

California Current. Calif. Coop. Oceanic Fish. Invest. Rep. 11:157-186.

Mason, J.E. and A. Bakun. 1986. Upwelling index update, U.S. west coast, 33N-48N

latitude. U.S. Dep. Commer., NOAA Tech. Memo., NOAA-TM-NMFS-SWFC-

67, 81 p.

McConnaughey, R.A., D.A. Armstrong, B.M. Hickey, and D.R. Gunderson. 1992.

Juvenile Dungeness crab (Cancer magister) recruitment variability and oceanic

transport during the pelagic larval phase. Can. J. Fish. Aquat. Sci.

49:2028-2044.

Nelson, C.S. 1977. Wind stress and wind-stress curl over the California Current. U.S.

Dep. Commer., NOAA Tech. Rep., NMFS SSRF-714, 87 p.

Nickelson, T.E. 1986. Influences of upwelling, ocean temperature, and smolt abundance

on marine survival of coho salmon (Oncorhynchus kisutch) in the Oregon

Production Area. Can. J. Fish. Aquat. Sci. 43:527-535.

Parrish, R.H., C.S. Nelson, and A. Bakun. 1981. Transport mechanisms and

reproductive success of fishes in the California Current. Biol. Oceanogr.

1:175-203.

Parrish, R.H. and A.D. MacCall. 1978. Climate variation and exploitation in the Pacific

mackerel fishery. Cal. Dep. Fish and Game, Fish Bull. 167. 110 pp.

Parrish, R.H. and D.L. Mallicoate. 1995. Variation in the condition factors of California

pelagic fishes and associated environmental factors. Fish. Oceanogr. 4:171-190.

Peterson, W.T. and C.B. Miller. 1977. Seasonal cycle of zooplankton abundance and

species composition along central Oregon coast. Fish. Bull. 75:717-724.

21

Robinson, M.K. 1976. Atlas of North Pacific Ocean: monthly mean temperatures and

mean salinities of the surface layer. Ref. Publ. 2, Naval Oceanographic Office,

Washington, DC. 173 p.

Ryther, J.H. 1969. Photosynthesis and fish production in the sea. Science 166:72-76.

Smith, R.L. 1968. Upwelling. Oceanogr. Mar. Biol. Ann. Rev. 6:11-46.

Sverdrup, H.U., M.W. Johnson, and R.H. Fleming. 1942. The oceans, their physics,

chemistry, and general biology. Prentice-Hall, New York, 1087 p.

Thomson, R.E. and D.M. Ware. 1996. A current index of ocean variability. J. Geophys.

Res. 101:14297-14310.

Traganza, E.D., J.C. Conrad, and L.C. Breaker. 1981. Satellite observations of a

cyclonic upwelling system and giant plume in the California Current. In F.A.

Richards (ed.), Coastal Upwelling, Amer. Geophys. Union, Washington, DC. p.

228-241.

van Geen, A. and D.M. Husby. 1996. Cadmium in the California Current system: tracer

of past and present upwelling. J. Geophys. Res. 101:3489-3507.

VenTresca, D.A., R.H. Parrish, J.L. Houk, M.L. Gingras, S.D. Short, and N.L. Crane.

1995. El Nino effects on the somatic and reproductive condition of blue rockfish,

Sebastes mystinus. Calif. Coop. Oceanic Fish. Invest. Rep. 36:167-174.

Walsh, J.J., T.E. Whitledge, J.C. Kelley, S.A. Huntsman, and R.D. Pillsbury. 1977.

Further transition states of the Baja California upwelling system. Limnol.

Oceanogr. 22:264-280.

Wroblewski, J.S. 1977. A model of phytoplankton plume formation during variable

Oregon upwelling. J. Mar. Res. 35:357-394.

Wooster, W.S. and J.L. Reid, Jr. 1963. Eastern Boundary Currents. p. 253-280. In

M.N. Hill (ed.), The Sea, Vol. 2. Interscience, New York. 554 p.

This manuscript was prepared with the AGU LATEX macros v3.1.

22

APPENDIX A - ANNUAL CYCLES OF DAILY AND

MONTHLY UPWELLING INDICES

The following five pages show the annual cycle of upwelling at the 15 standard

locations. The diamonds denote the mean of the monthly upwelling indices for each

calendar month for the period 1967–91. The vertical bars denote ± one standard

deviation for each calendar month. The bold curve is a biharmonic fit to the daily

upwelling indices for the period 1967–91, estimated by a least-squares regression of the

daily data to an annual and semiannual harmonic signal (Equation 5). The shaded area

around the biharmonic curve denotes ± one standard error, calculated for each Julian

Day. Three locations are shown on each page, from north to south.

The units are metric tons per second per 100 m of coastline (or equivalently cubic

meters per second per 100 meters of coastline). These units may be thought of as the

average amount (in metric tons or cubic meters) of water upwelled through the bottom

of the Ekman layer each second along each 100 m of a straight line directed along the

dominant trend of the coast on a scale of about 200 miles. Because of uncertainties

in some of the constants employed, and for other reasons outlined in this and the

previous three related NOAA Technical Memoranda, these indices should be considered

as indicative of short-term relative fluctuations at a location rather than as quantitative

measures of absolute magnitude.

23

APPENDIX C - MONTHLY UPWELLING INDICES,

ANOMALIES AND STANDARDIZED ANOMALIES

The following five pages contain contours of the monthly upwelling indices, the

monthly anomalies, and the standard anomalies for each calendar month. The data

are contoured with time (in months) as the abscissa and latitude as the ordinate. The

anomalies are relative to the 25-year mean of the monthly values in each month for the

period 1967–91, and the standard anomalies are the anomalies divided by the standard

deviation for the calendar month. The monthly values are shaded, with darker shading

representing negative (downwelling) indices. The contour interval for the monthly values

is 100 cubic meters per second per 100 m of coastline. Negative anomalies are shaded.

The contour interval for the anomalies is 50 cubic meters per second per 100 m of

coastline. Monthly standardized anomalies greater than one, that is anomalies greater

than one standard deviation from the 25-year mean, are denoted with light shading.

Monthly standardized anomalies less than -1 are denoted with dark shading. The data

are broken into five ten-year periods for ease of presentation.

The units are metric tons per second per 100 m of coastline (or equivalently cubic

meters per second per 100 meters of coastline). These units may be thought of as the

average amount (in metric tons or cubic meters) of water upwelled through the bottom

of the Ekman layer each second along each 100 m of a straight line directed along the

dominant trend of the coast on a scale of about 200 miles. Because of uncertainties

in some of the constants employed, and for other reasons outlined in this and the

previous three related NOAA Technical Memoranda, these indices should be considered

as indicative of short-term relative fluctuations at a location rather than as quantitative

measures of absolute magnitude.

45




1946 1947 1948 1949 1950 1951 1952 1953 1954 1955

1

-1

MONTHLY UPWELLING INDEX

MONTHLY ANOMALIES

MONTHLY STANDARDIZED ANOMALIES

500

400

300

200

100

0

-100

-200

-300

-400

-500

300

200

100

0

-100

-200

-300




1956 1957 1958 1959 1960 1961 1962 1963 1964 1965

1

-1


MONTHLY ANOMALIES


500

400

300

200

100

0

-100

-200

-300

-400

-500

300

200

100

0

-100

-200

-300




1966 1967 1968 1969 1970 1971 1972 1973 1974 1975

1

-1


MONTHLY ANOMALIES


500

400

300

200

100

0

-100

-200

-300

-400

-500

300

200

100

0

-100

-200

-300



1

-1


MONTHLY ANOMALIES

500

400

300

200

100

0

-100

-200

-300

-400

-500

300

200

100

0

-100

-200

-300


1976 1977 1978 1979 1980 1981 1982 1983 1984 1985





1986 1987 1988 1989 1990 1991 1992 1993 1994 1995

1

-1


MONTHLY ANOMALIES


500

400

300

200

100

0

-100

-200

-300

-400

-500

300

200

100

0

-100

-200

-300

coastal upwelling indices, west coast of north america, 1946-95

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